Alicia Klinefelter

Alicia Klinefelter joined NVidia in January 2017 and is currently a Research Scientist in the ASIC and VLSI research group. She completed her Ph.D. in Electrical Engineering at the University of Virginia, Charlottesville, VA, in 2015. Her Ph.D. thesis explored VLSI architectures for digital signal processing on energy-constrained SoCs and was completed under the guidance of Professor Ben Calhoun.  Her research interests include ultra-low-power circuit design, sub and near-threshold design techniques for DSPs, arithmetic and elementary function circuits, approximate computing, and design effort reduction.

NVIDIA Papers Win First and Second Best Paper Awards at HPG 2016

Monday, June 20, 2016

Best paper:

Anton S. Kaplanyan, Stephen Hill, Anjul Patney, and Aaron Lefohn, "Filtering Distributions of Normals for Shading Antialiasing"

Second Best Paper:

Chris Wyman, "Exploring and Expanding the Continuum of OIT Algorithms"

NVIDIA Co-Authored Paper Wins Best Paper Presentation at I3D 2017

Saturday, February 25, 2017

Morgan McGuire, Michael Mara, Derek Nowrouzezahrai, and David Luebke "Real-Time Global Illumination using Precomputed Light Field Probes"

NVIDIA Co-Authored Paper Wins Best Paper Award at IEEE Virtual Reality 2017

Saturday, March 18, 2017

David Dunn, Cary Tippets, Kent Torell, Petr Kellnhofer, Kaan Akşit, Piotr Didyk, Karol Myszkowski, David Luebke, and Henry Fuchs "Wide Field of View Varifocal Near-Eye Display using See-Through Deformable Membrane Mirrors"

NVIDIA Co-Authored Paper Wins Best Paper Award at IPDPS 2017

Monday, May 29, 2017

Benjamin Klenk, Holger Froening, Hans Eberle and Larry Dennison "Relaxations for High-Performance Message Passing on Massively Parallel SIMT Processors"

2017 Grad Fellows

NVIDIA Graduate Fellowship Results for 2017

We are excited to announce the 2017 NVIDIA Graduate Fellowship recipients!

We know that there is incredibly important work taking place at universities worldwide, and the NVIDIA Graduate Fellowship Program allows us to demonstrate our commitment to academia in supporting research that spans all areas of computing innovation. In particular this year, emphasis was given to students pushing the envelope in artificial intelligence, deep neural networks, autonomous vehicles, and related fields.

A unistable polyhedron with 14 faces

Unistable polyhedra are in equilibrium on only one of their faces. The smallest known homogeneous unistable polyhedron to date has 18 faces. Using a new optimization algorithm, we have found a unistable polyhedron with only 14 faces, which we believe to be a lower bound. Despite the simplicity of the formulation, computers were never successfully used for solving this problem due to the seemingly insurmountable dimensionality of the underlying mathematical apparatus.

Infinite Resolution Textures

We propose a new texture sampling approach that preserves crisp
silhouette edges when magnifying during close-up viewing, and benefits
from image pre-filtering when minifying for viewing at farther
During a pre-processing step, we extract curved silhouette edges from
the underlying images. These edges are used to adjust the texture
coordinates of the requested samples during magnification. The
original image is then sampled -- only once!

Phenomenological Transparency

Translucent objects such as fog, clouds, smoke, glass, ice, and liquids are pervasive in cinematic environments because they frame scenes in depth and create visually-compelling shots.

Hashed Alpha Testing

Renderers apply alpha testing to mask out complex silhouettes using alpha textures on simple proxy geometry. While widely used, alpha testing has a long-standing problem that is underreported in the literature, but observable in commercial games: geometry can entirely disappear as alpha mapped polygons recede with distance.


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